This invention relates to a method and apparatus for handling parts ejected from an injection molding machine. More particularly, in one aspect, the invention is directed to a system whereby data molded into the ejected part is used to provide useful feedback for the molding process. In another aspect, molded parts formed in a multiple molding die are ejected from the die in a manner to maintain the relative sequential or matrix organization so that useful feedback information can be generated. This system is particularly useful with subsequent machine vision and inspection applications wherein, for example, defects in the molded parts can be neurally learned and additional cognitive steps taken to improve the process.
While the invention is particularly directed to the art of injection molding machines, and will thus be described with specific reference thereto, it will be appreciated that the invention may have usefulness in other fields and applications including other molding applications.
By way of background, in the manufacturing process of injection molding, or other types of molding, whereby multiple parts are made per press stroke, or per shot, the parts are typically ejected from the molds such that they fall into a randomly organized jumbled pile. For example, if an injection molding die is making 40 parts per shot than each time the molding die is open, typically those 40 parts would be ejected in mass and would fall onto a conveyor which would bring them out and drop them into the bulk transport containers. This scenario is played out in tens of thousands of injection molding machine operations worldwide and is perfectly satisfactory for many manufacturing situations.
Another unloading scenario that is often used is that of robotic retrieval of components from the tooling. Robots can be used for many reasons some of which are that the components might be too large to drop through and handle properly or they may be damaged by dropping them and bulk conveyor handling. Or that the components need extra cooling time before they are allowed to be in contact with other components to prevent sticking and/or damage to the components. Sometimes robots are used to maintain the correct orientation or ordering of the components, or as a labor reduction technique or as a part of an overall automated system.
More and more attention is being paid within all of manufacturing but certainly within the plastics industries to process control. There are many different methodologies and techniques for monitoring the process in the various types of molding machinery, including injection molding. Monitoring pressure and flow and temperature and viscosity and many other parameters which have a relationship to the quality of the molding process. One of the technologies that is being used increasingly is the technology of machine vision or optical inspection techniques because of the intelligent and comprehensive nature of the kinds of the inspections that can be done.
Machine vision systems are generally comprised of a lighting system to light a specimen and a camera and lens for sensing light reflected therefrom. A processing means is also provided to implement suitable algorithms. A digitized image is formed from an image received by the camera. The data of this image is then available for use in, for example, controlling a robot arm, identifying the specimen, or determining whether the specimen is acceptable to specified standards with respect to, for example, flaws, process variations, or dimensional variations. The data can also be used (as is proposed herein) for feedback and process control. An exemplary machine vision system is shown and described in U.S. Pat. No. 4,882,498 to Cochran et al, which is incorporated herein by reference.
Unfortunately, from a practical standpoint, it is not presently possible to do a vision inspection while the product is being molded because of the high temperature, high pressure environment inside a tool cavity. Therefore, vision inspection is typically done after the injection molding die as an example would open thus, exposing the part. Unfortunately, because the injection molded part may still be engaged with a portion of the tooling when the dies are separated, there is only a limited amount of inspection that can be easily done at the point of die separation. Often, even if the desired features can be observed when the dies are parted but before the components are ejected from the tooling, it is a difficult machine vision inspection task for a variety of reasons.
The manufacturer does not want to slow down the manufacturing process by leaving the die in a fixed open position. Since there are multiple die cavities and therefore, multiple components to be inspected with each shot, it is necessary to either have many cameras, each focused at its own respective component, or group of subcomponents, or the resolution is poor because with a more limited number of cameras, the respective number of pixels falling on any given component is reduced, there are angle of view problems and challenges, there are space and mounting constraints, and optimum illumination is extremely difficult. While there are certainly some attributes that can be inspected optically or by machine vision, while the part is still in the separated tool, it can be easily understood that it is very limited and a comprehensive inspection can not usually be undertaken. It is therefore much more desirable in order to do a comprehensive inspection to do that inspection after the parts have been ejected from the molding die. It is well known in the molding industry, especially in injection molding, that there are many different kinds of defects that are produced during the injection molding process. The Society of Manufacturing Engineers has a CD-ROM training program that they have been advertising which is entitled “Trouble Shooting Injection Molding Problems”. It lists the following 24 different defects which it teaches how to trouble shoot. The defects listed are: black specs, blisters, blush, bowing, brittleness, bubble/voids, burn marks, clear spots, cloudy appearance, contamination, cracking, crazing, delamination, discoloration, flash, flow lines, low gloss, jetting, knit lines, non-fill/short shot, excessive shrinkage, sink marks, splay and warpage.
Additionally, there is a wide variety of dimensional defects that can occur in injection molded parts. It is very desirable to do machine vision or optical inspection to look for some or all of the above defects and reject the faulty parts. Just providing that function is often thoroughly economically justifiable so that quality can be monitored by way of sorting out bad product. But to make an inspection system even more valuable to an injection molding manufacturer, it is desirable to be able to provide statistical process control information so that the process can be corrected such that it does not manufacture the faulty parts. Sometimes the machine vision inspection information alone is not enough to make the call on what is going out of control in the process and may need to be combined with other sensory information. Regardless of whether only the machine vision or optical inspection data is used to make the determination of process variation or whether it is combined with other sensory information from the process, it must be correlated back to which molding cavity or cavities is responsible for producing the bad component(s).
If the molded parts are simply ejected such that they fall in a non-organized group onto a shoot or conveyor, then relevant process control information pointing to which mold cavity the molded component came from is lost.
The present invention contemplates a new approach to handling parts ejected from injection molding machines which resolves the above-referenced difficulties and others.